英文摘要
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As to the era of big data, the volume of data has exploded in our lives. If data can be analyzed effectively, the results will create significant values in business. Recently, as social media blooming, people are used to sharing opinions on social media. Therefore, the data analytics for social media is in the spotlight. Furthermore, the effect of social media is significant in the field of politics because internet comments are closely related to the image of politicians. If unstructured data can be analyzed, the results will become important in evaluating politicians. Big data and sentiment analysis are developing, researchers have applied sentiment analysis to evaluate politicians based on the English Lexicon but none of them used Chinese Lexicon to conduct sentiment analysis. This study focuses on the candidate analysis of Taipei City Mayor Election in 2018. For the research, the researcher establishes the Chinese Characteristics Keyword Lexicon on the basis of sentiment analysis, analyzes the internet comments on the Facebook fan pages of three candidates and calculates text sentiment scores on the five dimensions in order to evaluate the performance of politicians on each dimension. The innovative way of data mining and sentiment analysis for politicians' evaluation provide different voices and perspectives for campaign teams to map strategies.
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